Computers and Math from Science Daily Feed

A recently created RoboBee is now outfitted with its most reliable landing gear to date, inspired by one of nature's most graceful landers: the crane fly. The team has given their flying robot a set of long, jointed legs that help ease its transition from air to ground. The robot has also received an updated controller that helps it decelerate on approach, resulting in a gentle plop-down.

According to new research next-generation DNA sequencing (NGS) -- the same technology which is powering the development of tailor-made medicines, cancer diagnostics, infectious disease tracking, and gene research -- could become a prime target for hackers.

Physicists have created a compact laser that emits extremely bright, short pulses of light in a useful but difficult-to-achieve wavelength range, packing the performance of larger photonic devices onto a single chip.

Platforms such as iNaturalist and eBird encourage people to observe and document nature, but how accurate is the ecological data that they collect? A new study shows that citizen science data from iNaturalist and eBird can reliably capture known seasonal patterns of bird migration in Northern California and Nevada -- from year-round residents such as California Scrub-Jays, to transient migrants such as the Western Tanager and the Pectoral Sandpiper.

A team has developed an explainable AI model for automatic collision avoidance between ships.

Diamonds with certain optically active defects can be used as highly sensitive sensors or qubits for quantum computers, where the quantum information is stored in the electron spin state of these colour centeres. However, the spin states have to be read out optically, which is often experimentally complex. Now, a team has developed an elegant method using a photo voltage to detect the individual and local spin states of these defects. This could lead to a much more compact design of quantum sensors.

Researchers share a model that identifies the optimal location for bowling ball placement. Employing a system of six differential equations derived from Euler's equations for a rotating rigid body, their model creates a plot that shows the best conditions for a strike. The model accounts for a variety factors, including the thin layer of oil applied to bowling lanes, the motion of the subtly asymmetric bowling ball, and a 'miss-room' to allow for human inaccuracies.

Researchers use mathematical modeling to probe whether cohesive communities are more resilient to extreme events, finding that emotional intensity and levels of stress play a big role.

A groundbreaking open-source computer program uses artificial intelligence to analyze videos of patients with Parkinson's disease and other movement disorders. The tool, called VisionMD, helps doctors more accurately monitor subtle motor changes, improving patient care and advancing clinical research.

Neural networks are one typical structure on which artificial intelligence can be based. The term neural describes their learning ability, which to some extent mimics the functioning of neurons in our brains. To be able to work, several key ingredients are required: one of them is an activation function which introduces nonlinearity into the structure. A photonic activation function has important advantages for the implementation of optical neural networks based on light propagation. Researchers have now experimentally shown an all-optically controlled activation function based on traveling sound waves. It is suitable for a wide range of optical neural network approaches and allows operation in the so-called synthetic frequency dimension.

Researchers have developed a new forecasting model that helps companies more accurately estimate how many customers are interested in a product -- even when key data is missing. The study introduces a mathematical modeling method that enables businesses to estimate customer interest beyond just completed transactions and traditional forecasting techniques. The approach offers a more precise way to understand demand, optimize operations and improve decision-making.

A new study by neuroscientists shows that our brain deals with different forms of visual uncertainty during movements in distinct ways. Depending on the type of uncertainty, planning and execution of movements in the brain are affected differently. These findings could help to optimize brain-computer interfaces that, for example, help people with paralysis to control prostheses or computers with their thoughts alone.

Engineers discovered a way to move heat ultrafast using crystal waves, offering a breakthrough in cooling advanced electronics.

Researchers have developed a pioneering, sustainable method for producing cadmium-based quantum dots (QDs) in water using a biocompatible chalcogen source. This fully aqueous, continuous flow process avoids harmful organic solvents and offers enhanced safety, scalability, and environmental performance. A collaboration led to the creation of a water-soluble chalcogen transfer agent inspired by peptide chemistry. Real-time Raman spectroscopy enabled detailed analysis of reaction mechanisms. The new system improves productivity while reducing waste and energy use. Although cadmium QDs are efficient, their toxicity remains a concern, prompting the team to explore greener alternatives. This innovation marks a significant step toward responsible, large-scale nanomaterial production.

Researchers have developed an AI tool that creates synthetic yet medically accurate models of fibrotic heart tissue (heart scarring), aiding treatment planning for atrial fibrillation (AF) patients. The study could lead to more personalized care for patients affected by this common heart rhythm disorder.

Using electrodes in a fluid form, researchers have developed a battery that can take any shape. This soft and conformable battery can be integrated into future technology in a completely new way.

Pushing the limits of structured light, applied physicists report a new type of optical vortex beam that not only twists as it travels but also changes in different parts at different rates to create unique patterns. The way the light behaves resembles spiral shapes common in nature.

Quasicrystals are intriguing materials with long-range atomic order that lack periodicity. It has been a longstanding question whether antiferromagnetism, while commonly found in regular crystals, is even possible in quasicrystals. In a new study, researchers have finally answered this question, providing the first definitive neutron diffraction evidence of antiferromagnetism in a real icosahedral quasicrystal. This discovery opens a new research area of quasiperiodic antiferromagnets, with potential applications in spintronics.

In a striking demonstration of molecular control, a team of scientists has harnessed light to reverse the twist in self-assembling molecules. The study identifies how trace residual aggregates in photo-responsive azobenzene solutions can reverse helical chirality through secondary nucleation. By using precise control of ultraviolet and visible light, the researchers could switch between the rotation of helices, offering a breakthrough for novel materials with tunable properties.

Using artificial intelligence shortens the time to identify complex quantum phases in materials from months to minutes, finds a study. The breakthrough could significantly speed up research into quantum materials, particularly low-dimensional superconductors.